The SPRT chart for monitoring a proportion

被引:17
|
作者
Reynolds, MR [1 ]
Stoumbos, ZG
机构
[1] Virginia Polytech Inst & State Univ, Dept Stat, Blacksburg, VA 24061 USA
[2] Virginia Polytech Inst & State Univ, Dept Forestry, Blacksburg, VA 24061 USA
[3] Rutgers State Univ, Dept Management Sci & Informat Syst, Newark, NJ 07102 USA
[4] Rutgers State Univ, Rutgers Ctr Operat Res, Newark, NJ 07102 USA
关键词
D O I
10.1080/07408179808966494
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A control chart based on applying a sequential probability ratio test (SPRT) at each sampling point is considered for the problem of monitoring a process proportion p. This SPRT chart can be applied in situations in which items are inspected one by one, and the results of each inspection can be conveniently recorded before the next item is inspected. Some corrected diffusion theory approximations are given for the statistical properties of the SPRT and the SPRT chart. These approximations are very accurate and provide a simple method for designing an SPRT chart for practical applications. The sample size for the SPRT chart at a particular sampling time depends on the observations at that time, but the chart can be designed to have a specified average sampling rate when the process is in control. When there is a small shift in p, the average sampling rate per unit time will increase, but for a large shift inp the average sampling rate will decrease. For a given in-control average sampling rate and a given false alarm rate, the SPRT chart will detect changes inp much faster than the standard,p-chart, which has traditionally been used for monitoring p. The SPRT chart will also detect changes in p much faster than the CUSUM chart for p. Thus, the SPRT chart can be used in place of traditional control charts to provide faster detection of changes in p or to reduce the sampling effort required to provide a given detection capability.
引用
收藏
页码:545 / 561
页数:17
相关论文
共 50 条
  • [1] An improved SPRT control chart for monitoring process mean
    Yanjing Ou
    Zhang Wu
    Songlin Chen
    Ka Man Lee
    [J]. The International Journal of Advanced Manufacturing Technology, 2010, 51 : 1045 - 1054
  • [2] An improved SPRT control chart for monitoring process mean
    Ou, Yanjing
    Wu, Zhang
    Chen, Songlin
    Lee, Ka Man
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2010, 51 (9-12): : 1045 - 1054
  • [3] A new SPRT chart for monitoring process mean and variance
    Ou, Yanjing
    Wu, Zhang
    Goh, Thong Ngee
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2011, 132 (02) : 303 - 314
  • [4] Optimal average sample number of the SPRT chart for monitoring fraction nonconforming
    Haridy, Salah
    Wu, Zhang
    Lee, Ka Man
    Bhuiyan, Nadia
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2013, 229 (02) : 411 - 421
  • [5] A Binomial GLR Control Chart for Monitoring a Proportion
    Huang, Wandi
    Reynolds, Marion R., Jr.
    Wang, Sai
    [J]. JOURNAL OF QUALITY TECHNOLOGY, 2012, 44 (03) : 192 - 208
  • [6] The SPRT sign chart for process location
    Mahadik, Shashibhushan B.
    Godase, Dadasaheb G.
    [J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2023, 52 (07) : 2276 - 2290
  • [7] Optimization Design of the SPRT Control Chart
    Ou, Yanjing
    Wu, Zhang
    [J]. 16TH ISSAT INTERNATIONAL CONFERENCE ON RELIABILITY AND QUALITY IN DESIGN, 2010, : 16 - 20
  • [8] The Generalized Likelihood Ratio Chart for Monitoring a Proportion with Autocorrelation
    Wang, Ning
    Reynolds, Marion R., Jr.
    [J]. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2015, 31 (06) : 1023 - 1034
  • [9] Bootstrap beta control chart for monitoring proportion data
    Chowdhury, Shovan
    Kundu, Amarjit
    Modok, Bidhan
    [J]. INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT, 2022, 39 (10) : 2354 - 2377
  • [10] A CUSUM Chart for Monitoring a Proportion with Autocorrelated Binary Observations
    Mousavi, Shabnam
    Reynolds, Marion R., Jr.
    [J]. JOURNAL OF QUALITY TECHNOLOGY, 2009, 41 (04) : 401 - 414